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UID:pretalx-pyconde-pydata-2026-AGYLTV@pretalx.com
DTSTART;TZID=CET:20260415T142000
DTEND;TZID=CET:20260415T155000
DESCRIPTION:Python has become the dominant language for scientific computin
 g and data science\, largely due to powerful array libraries that enable h
 igh-performance numerical computation. This tutorial introduces array-orie
 nted programming as a paradigm and surveys the modern Python array ecosyst
 em.\n\nWe'll explore when and how to use different array libraries: NumPy 
 for general-purpose array operations\, JAX for automatic differentiation\,
  just-in-time compilation of array-oriented code\, and GPU acceleration\, 
 Numba for just-in-time compilation of imperative code\, and Awkward Array 
 for nested and irregular data structures. Through live demos\, we'll show 
 how to think in arrays\, discuss the limitations of array-oriented program
 ming\, and demonstrate how JIT compilation addresses these challenges.\n\n
 Whether you're analyzing data\, building machine learning models\, or doin
 g scientific simulations\, understanding the strengths and trade-offs of e
 ach library will help you choose the right tool for your problem.
DTSTAMP:20260523T180036Z
LOCATION:Dynamicum [Ground Floor]
SUMMARY:Array-Oriented Programming in Python: Libraries\, Techniques\, and 
 Trade-offs - Iason Krommydas
URL:https://pretalx.com/pyconde-pydata-2026/talk/AGYLTV/
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